Proceedings Paper

There are two problems when associating multiple targets in remote sensing images: Firstly, with low temporal
resolution observation, the target's kinematic state cannot be estimated accurately and the classical Kalman filtering
association algorithms are no more applicable. Secondly, the classical image feature-based target matching algorithms
cannot deal with the illegibility of multiple targets' correspondence, which don't take into account the uncertainty of
feature extraction. To resolve above problems, a novel multiple targets association method based on Multi-scale
Autoconvolution(MSA) features matching and global association cost optimization through simulated annealing (SA)
algorithm is proposed. Experiments with remote sensing images show the applicability of the method for multiple targets
association.